Triple
T2802368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Puebla |
E53175
|
entity |
| Predicate | FrenchCommander |
P19844
|
FINISHED |
| Object |
Charles de Lorencez
Charles de Lorencez was a French general best known for leading the ill-fated French assault against Mexican forces at the Battle of Puebla in 1862.
|
E444941
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Charles de Lorencez | Statement: [Battle of Puebla, FrenchCommander, Charles de Lorencez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charles de Lorencez Context triple: [Battle of Puebla, FrenchCommander, Charles de Lorencez]
-
A.
Henri Contet
Henri Contet was a French lyricist known for writing songs for prominent chanson artists in the mid-20th century.
-
B.
Léon Boyer
Léon Boyer was a French civil engineer best known for designing major 19th-century railway structures, including the Garabit Viaduct.
-
C.
François Dupeyron
François Dupeyron was a French film director and screenwriter known for his humanistic, character-driven dramas.
-
D.
Henri Lebasque
Henri Lebasque was a French post-impressionist painter known for his luminous use of color and intimate domestic and landscape scenes.
-
E.
Louis Jeantet
Louis Jeantet was a Swiss businessman and philanthropist whose foundation established one of Europe’s most prestigious awards in biomedical research.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Charles de Lorencez Triple: [Battle of Puebla, FrenchCommander, Charles de Lorencez]
Generated description
Charles de Lorencez was a French general best known for leading the ill-fated French assault against Mexican forces at the Battle of Puebla in 1862.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Charles de Lorencez Target entity description: Charles de Lorencez was a French general best known for leading the ill-fated French assault against Mexican forces at the Battle of Puebla in 1862.
-
A.
Henri Contet
Henri Contet was a French lyricist known for writing songs for prominent chanson artists in the mid-20th century.
-
B.
Léon Boyer
Léon Boyer was a French civil engineer best known for designing major 19th-century railway structures, including the Garabit Viaduct.
-
C.
François Dupeyron
François Dupeyron was a French film director and screenwriter known for his humanistic, character-driven dramas.
-
D.
Henri Lebasque
Henri Lebasque was a French post-impressionist painter known for his luminous use of color and intimate domestic and landscape scenes.
-
E.
Louis Jeantet
Louis Jeantet was a Swiss businessman and philanthropist whose foundation established one of Europe’s most prestigious awards in biomedical research.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab495a90788190941b6917e1eca3a6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abde12b33481908b276760a922db9c |
completed | March 7, 2026, 8:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b6720e877481908d870653bbb09820 |
completed | March 15, 2026, 8:47 a.m. |
| NEDg | Description generation | batch_69b6727e314c819096e6aa6cda67d6f7 |
completed | March 15, 2026, 8:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b672c3816c8190806144d98d51a484 |
completed | March 15, 2026, 8:50 a.m. |
Created at: March 6, 2026, 9:58 p.m.